Product Crystal Size Research Articles

Simultaneous recovery of ammonium sulfate and ice from aqueous solution using eutectic freeze crystallization process

This study investigated the feasibility of eutectic freeze crystallization (EFC) process for ammonium sulfate (AS) salt recovery from 41 wt% AS solution. The EFC experiments were conducted using a 1 L double-jacketed crystallizer coupled with a recirculating chiller under varying freezing time, seed mass and seed size. The EFC process demonstrated successful AS salt recovery and water purification with the highest ice purity attained at 96.28 %. The construction of a binary AS-water phase diagram allowed the determination of the eutectic temperature, which was found to be −19.06 °C at 40 wt% of AS solution. The results indicated that the increase in freezing time enhanced the AS nucleation rate, growth rate, yield and mean product crystal size. The introduction of seeding not only provided well-controlled crystal nucleation and growth during EFC process, but also promoted the formation of larger, well-structured crystals and reduced agglomeration. Overall, the EFC process is a viable and promising option for recovering AS from wastewater, which offers high potential towards achieving zero liquid discharge goal, i.e. a sustainable and efficient approach in managing industrial effluent rich in ammonium and sulfate contaminants.

Development of Continuous Additive-Controlled MSMPR Crystallization by DoE-Based Batch Experiments.

Additive-controlled crystallization is a promising method to improve crystal morphology and produce solid drug particles with the desired technological and pharmacological properties. However, its adaptation to continuous operation is a hardly researched area. Accordingly, in this work, we aimed to come up with a methodology that provides the systematic and fast development of a continuous three-stage MSMPR cascade crystallizer. For that, a cooling crystallization of famotidine (FMT) from water, in the presence of a formulation additive, poly(vinylpyrrolidone) (PVP-K12), was developed. Process parameters with a significant impact on product quality and quantity were examined in batch mode through a 24-1 fractional factorial design for the implementation of additive-controlled continuous crystallization. These batch experiments represented one residence time of the continuous system. Based on the statistical analysis, the residence time (RT) had the highest effect on yield, while the polymer amount was critical from the product polymorphism, crystal size, and flowability points of view. The values of critical process parameters in continuous operation were fixed according to the batch results. Two continuous cooling crystallization experiments were carried out, one with 1.25 w/wFMT% PVP-K12 and one with no additive. A mixture of FMT polymorphs (Form A and Form B) crystallized without the additive through five residence times (>6.5 h) with 70.8% overall yield. On the other hand, the additive-controlled continuous experiment resulted pure and homogeneous Form A product with excellent flowability. The system could be operated for >6.5 h without clogging with a 71.1% overall yield and a 4-fold improvement in productivity compared to its batch equivalent.

Application of Anti-Solvent Crystallization for High-Purity Potash Production from K-Feldspar Leaching Solution

Potassium-containing feldspars provide a high potential for producing potash, a product with widespread use in agriculture. The present work assesses applying the anti-solvent crystallization method for the purification and recovery of high-purity muriate of potash (KCl) from feldspar leaching solutions. Initially, screening experiments were carried out on a synthetic leaching solution with the aim of analyzing the crystallization behavior of key components. Screening experiments were performed using five anti-solvents, namely methanol, ethanol, acetone, 2-propanol, and ethylene glycol. Acetone and 2-propanol were viable options for crystallization of potassium chloride. Then, the effects of anti-solvent ratio (O/A), time, and anti-solvent addition rate on potassium-chloride crystallization were further investigated using acetone and 2-propanol. A recovery of 83% of potassium was achieved when using acetone at the O/A of 5 with the addition rate of 10 mL/min, at room temperature with a hold time of 180 min. The optimum conditions for 2-propanol were determined to be similar, except for using a 5 mL/min addition rate for 79% recovery. The final muriate of potash products had a purity of over 99.9% using either of the anti-solvent. However, differences in morphology and crystal size of products were observed. Acetone-formed potash crystals were aggregates of cubic crystals with an average size of 3 microns, while 2-propanol-formed potash crystals were 20 microns in size as cubic particles with a hollow core. Despite having almost the same performance in potassium recovery, acetone was found to be a more feasible anti-solvent for potash recovery due to simpler downstream solvent recovery.

Continuous Crystallization Process of Cefminox Sodium in MSMPR Crystallizer

Continuous crystallization technology has attracted rising attention from chemists and material scientists. In this paper, cefminox sodium is selected as a model drug for consecutive antisolvent crystallization using a multistage mixed suspension mixed product removal (MSMPR) crystallizer. The effects of operating parameters on the product crystal particle size, crystal habit, and yield under steady-state conditions are investigated in detail: operating parameters such as the initial concentration of the crystallization solution, the volume ratio of the crystallization solution to antisolvent, the total flow rate, the amount of seed crystals added, the crystallization temperature, and the mixing rate. The kinetic solubility data of cefminox sodium in two binary aqueous mixed solvents at 278.15–303.15 K are determined by laser dynamic method, and two empirical models are subsequently borrowed to fit the obtained data. This work provides a new crystallization process for cefminox sodium. After optimization, the mass yield is increased to 89.11%, the average particle size Dv(50) is about 164 µm.

Data-Driven Operation Modeling and Optimal Design for Batch Cooling Crystallization with a Case Study on β-LGA

In this paper, a data-driven modeling and optimization method is proposed for batch operation of the cooling crystallization process based on the design of experiments (DoE) in the operation ranges of cooling rate and initial solution supersaturation. The proposed model reflecting a mapping relationship between the manipulated variables of operating conditions and the product crystal size distribution (CSD) is established by two classes of basis functions, one is the wavelet basis function for reshaping the CSD and the other is the polynomial basis function for weighting the chosen wavelet basis functions to reflect the nonlinear relationship between the manipulated variables and the size distribution of product crystals. Meanwhile, a fractional factorial design of DoE is presented to reduce the number of experiments for the above modeling, in comparison with the classical full factorial design. The optimal operating conditions are designed by introducing a comprehensive objective function that combines the information entropy of the product CSD and the ratio of desired product yield with respect to the target crystal size. A particle swarm optimization algorithm with guaranteed convergence is given to solve the nonconvex optimization problem based on the established CSD prediction model. Simulation studies and experiments on the batch seeded β-form L-glutamic acid (LGA) crystallization process are conducted to demonstrate the effectiveness and advantage of the proposed method.

Kinetic characteristics of evaporative crystallization desalination of acidic high-salt wastewater

CLT acid (2-amino-4-methyl-5-chlorobenzenesulfonic acid) is a red organic pigment intermediate, which is widely used in textile printing and dyeing industry, but a large amount of acidic MgSO4 high-salt wastewater will be generated during the production process. Direct discharge not only wastes sulfates in wastewater, but also damages the environment. In this paper, a new treatment process is developed to separate and recover MgSO4 from high-salt wastewater by thermal evaporation crystallization method, which realizes the resource utilization and ensures the treatment effect. Through the evaporative crystallization kinetic experiment and the pilot experiment of acidic MgSO4 high-salt wastewater, the influence of operating conditions on the product crystal size and crystal size distribution was investigated. The results show that the crystal growth is completed when the residence time is 40 min, the stirring speed is 200 r/min, and the seed content is 3 g/L. In industrial production, crystallization and recrystallization should be carried out after removing organic matters. When the concentration ratio is 1.6, the purity of MgSO4 crystal reach 96 %, and the resources can be maximized.

Online learning‐based predictive control of crystallization processes under batch‐to‐batch parametric drift

AbstractThis work considers a seeded fesoterodine fumarate (FF) cooling crystallization and presents the methodology and implementation of a real‐time machine learning modeling‐based predictive controller to handle batch‐to‐batch (B2B) parametric drift. Specifically, an autoencoder recurrent neural network‐based model predictive controller (AERNN‐MPC) is developed to optimize product yield, crystal size, and energy consumption while accounting for the physical constraints on cooling jacket temperature. Deviations in the kinetic parameters are considered in the closed‐loop simulations to account for the B2B parametric drift, and two error‐triggered online update mechanisms are proposed to address issues pertaining to the availability of real‐time crystal property measurements and are incorporated into the AERNN‐MPC to improve the model prediction accuracy. Closed‐loop simulation results demonstrate that the proposed AERNN‐MPC with online update, irrespective of the accessibility to real‐time crystal property data, achieves a desired closed‐loop performance in terms of maximizing product yield and minimizing energy consumption.

Insight into the Nucleation Mechanism of p-Methoxybenzoic Acid in Ethanol-Water System from Metastable Zone Width.

The metastable zone width (MSZW) of p-methoxybenzoic acid (PMBA) in an ethanol-water system was measured using the polythermal method. The nucleation order m obtained by the Nývlt’s model indicates the nucleation of PMBA following a progressive nucleation mechanism at low saturation temperature (m = 3.18–7.50) and an instantaneous nucleation mechanism at high saturation temperature (m = 1.46–2.55). Then, combined with the metastable zone experiment and the Sangwal model, we found that the MSZW and the interfacial energy reached the maximum when the mass fraction of ethanol was 0.8, which resulted in the smallest crystal product size. Meanwhile, the maximum and obtained based on the modified Sangwal model indicating the PMBA needs to overcome a higher nucleation barrier in the ethanol mass fraction of 0.8. Finally, we proposed a preferential strategy for adjusting MSZW by correlating the interfacial energy with the change in ethanol mass fraction, saturation temperature, and cooling rate, respectively.

Predictive Control of Batch Crystallization Process Using Machine Learning

This work develops a framework for building machine learning models and machine learning-based predictive control schemes for batch crystallization processes. We consider a seeded fesoterodine fumarate cooling crystallization and dissolution in a batch reactor and present the methodology and implementation of simulation, modeling, and controller design. Specifically, to address the experimental data scarcity problem, we first develop a population balance model (PBM) based on published kinetic parameters to describe the formation of crystals via nucleation, growth, and agglomeration. Then, recurrent neural network (RNN) models are developed using data from extensive simulations of the semi-empirical PBM under various operating conditions to capture the process dynamic behavior. The model predictive control (MPC) scheme using RNN models is developed to optimize the crystallization process in terms of product yield, crystal size, and energy consumption, while accounting for the constraints on the manipulated inputs. Through open- and closed-loop simulations, it is demonstrated that the RNN models well capture the process dynamics, and the RNN-based MPC achieves desired product yield and crystal size with significantly improved computational efficiency.

Production of Sucrose Crystals of Uni-Modal Size Distribution by Seeded Batch Cooling Crystallization

From sucrose aqueous solution of high viscosity, sucrose was crystallized by seeded cooling in a batch crystallizer. At low seed loadings, the product crystal size distribution (CSD) was wide-spread because of enormous secondary and primary nucleation. However, at high seed loadings, it became uni-modal, where the crystallization was dominated by seed growth with practically no secondary nucleation. Enough seeding was thus effective in suppressing nucleation even during batch crystallization with high viscosity solution. The volume mean size of the product crystals obtained at high seed loadings agreed with that calculated by a simple mass balance assuming growth-dominated crystallization with no change in the number of crystals.

Aplikasi Mesin Pemasak Minuman Rempah Jahe (Zingiber officinale) Dengan Pengaduk Otomatis di UKM Polanmadu

<p><em><strong>Cooking Machine Application of Ginger Drink (Zingiber officinale) with Automatic Stirrer at UKM Polanmadu</strong></em>. The trend of instant spice drinks that function to maintain the body’s immunity is growing rapidly in the era of the Covid-19 pandemic. Ginger, which is a spice with various benefits, has made many Small and Medium Enterprises (SMEs) industry players take advantage of this potential. One of them is the instant spice drink SME industry player "Polanmadu" which produces natural instant spice drinks. The processing of instant spice drinks is still done conventionally, making Polanmadu SMEs unable to reach consumer demands. The purpose of these activities was to the introduction of appropriate technology in the production of instant spice drinks to produce products with more guaranteed quality and able to generate additional income for partners. The application of the cooking machine is useful so that the stirring process which has been going on for 3 hours conventionally using human power is replaced with electric power so that it is more efficient and profitable. The implementation begins with identification, planning, assembling tools, testing tools, and introducing tools to the spice instant drink production unit. The result showed that the introduction of a spice instant drink cooking machine can produce 20% more crystal ginger extract, automatic stirring while at the same time speeding up the formation of crystals from 3 hours to 2.5 hours, and the product crystal size is more homogenous and an increase in profit of Rp906,000-/day. Overall, the introduction of this spice-cooking machine makes the productivity of SMEs for instant spice drinks increase in quality and quantity.</p>

Towards an enhanced control of protein crystallization: Seeded batch lysozyme crystallization in a meso oscillatory flow reactor

Protein crystallization has been shown as a viable alternative to conventional protein purification methods. However, the stochastic and spontaneous nature of the primary nucleation process makes protein crystallization difficult to control. An approach often used in the crystallization of small organic and inorganic molecules to improve the reproducibility of the process and better control the crystallization outcome is seeding. This study presents for the first time the investigation of seeding on batch protein crystallization in a meso oscillatory flow reactor (meso-OFR). Seeded and unseeded lysozyme batch crystallization experiments were carried out, where the influence of the initial lysozyme concentration (initial supersaturation) and the seed quantity on the onset of nucleation, crystal properties and yield was assessed. No major influence of the seed quantity on the product crystal size was verified for the initial lysozyme concentration of 20 mg·mL−1 (below the secondary nucleation threshold - SNT), while for the initial lysozyme concentration of 25 mg·mL−1 (above the SNT) the onset of nucleation and mean crystal size significantly decrease with increasing seed quantity. Further, crystal yield increases with both the initial lysozyme concentration and seed quantity. Overall, the results highlight seeding as a promising technique to improve control over the crystallization time and product crystal size.

Numerical Simulations of Seeded Batch Crystallization Demonstrating the Effect of Stochastic Nucleation on Crystal Product Quality

Numerical simulations of seeded batch cooling crystallization were performed to investigate the effect of stochastic nucleation on crystal quality parameters. In a typical deterministic mathematical model for crystallization, which contains population and mass balance equations, primary and secondary nucleation are regarded as Poisson processes in order to derive a stochastic model. In this study, these stochastic model equations were repeatedly solved to achieve a stochastic simulation, and statistical analysis of the results revealed differences in product quality when the simulations were run under certain conditions. In particular, the statistics, such as the mean and the coefficient of variation, of the product crystal size distribution were found to fluctuate as a result of stochastic primary and secondary nucleation. Further, stochastic primary nucleation was also found to be the source of the differences between the statistics obtained using the deterministic and stochastic simulations when the seed-loading ratio was very low. This difference was attributed to the growth of crystals when the total number of crystals was less than one, as well as the accompanying secondary nucleation, in the standard deterministic simulation. Thus, a novel deterministic model in which secondary nucleation does not occur until the total number of crystals reaches one was used, and the results and statistics were found to agree with those obtained using the stochastic numerical simulation. In addition, a stochastic model ignoring stochastic secondary nucleation omitted to predict the significant statistical fluctuations under certain conditions. Finally, the statistical fluctuations were predicted for several crystallizer scales, and crystallizer scale-up was found to reduce the fluctuations caused by stochastic primary and secondary nucleation.

Development of a triple impinging jet mixer for continuous antisolvent crystallization of acetylsalicylic acid reaction mixture

This study aims to develop a continuous antisolvent crystallization technique using a novel non-submerged triple impinging jet mixer for multiple feeding volume ratios to perform the direct procession of a flow acetylsalicylic acid (ASA) reaction mixture. The impinging jet mixer was supplemented by an overflow mixed suspension mixed product removal (MSMPR) crystallizer to provide a longer aging period for the crystals. The effect of temperature, residence time, and antisolvent to ASA solution ratio on product purity, yield, productivity, crystal size, and crystal size distribution was examined applying a 23 two-level full factorial experimental design. It was found that due to the intensive initial mixing achieved with triple impinging jet significantly smaller crystal size (<180 µm) with narrower unimodal crystal size distribution and higher maximum yield (83.1%) could be obtained compared to the conventional MSMPR technique. Furthermore, the developed continuous crystallization was accomplished in smaller equipment with the same productivity. Consequently, the processing of the ASA reaction mixture using a triple impinging jet mixer system enables the morphology modification and the direct connection of flow synthesis with continuous crystallization step.

Continuous enantioselective crystallization of chiral compounds in coupled fluidized beds

• Highly productive continuous enantioselective crystallization. • Exploitation of two coupled fluidized bed crystallizers. • Provision of narrow product crystal size distributions. • Validation of a reduced population balance model. • First results regarding high resolution CFD-DEM simulations. This review summarizes results of an interdisciplinary project devoted to improve the access to enantiopure components by applying an advanced continuous separation process exploiting the principle of kinetically controlled preferential crystallization within two coupled fluidized beds located in conically shaped tubular crystallizers. The process efficiently combines selective crystallization with integrated product classification. Along with summarizing the related literature, new original results are presented with respect to theoretical process description and experimental validation. Although only one chiral system is considered specifically, namely the separation of the enantiomers of a racemic mixture of asparagine monohydrate using water as solvent, general conclusions will be drawn to highlight the large potential of the process principle. The conceptual approaches presented are seen as useful tools for the development of productive continuously operating enantioselective crystallization processes. They are applicable to separate enantiomers of numerous chiral molecules.

Data-driven modeling of product crystal size distribution and optimal input design for batch cooling crystallization processes

In this paper, a novel data-driven model building method is proposed for predicting one-dimensional product crystal size distribution (CSD) or chord length distribution (CLD) of batch cooling crystallization processes, based on only batch run data. The proposed model relating the manipulated variable of cooling rate to the product CSD are constructed by two classes of basis functions, one is the wavelet basis function for reshaping the CSD and the other is the polynomial basis function for weighting the chosen wavelet basis functions to reflect the nonlinear relationship between the input and the density of individual crystal size among the product crystals. Correspondingly, a double-layer least-squares algorithm is established to estimate the model parameters, along with an adaptive strategy to determine the location and number of wavelet basis functions. By introducing an objective function that combines the information entropy of product CSD and the sample deviation of product crystals in each batch with respect to the target crystal size, the optimal input design of cooling rate for the desired product CSD is carried out by using a particle swarm optimization (PSO) algorithm to solve the non-convex optimization problem with the established CSD model. Simulation tests on the hen-egg-white lysozyme crystallization process along with experiments on the L-glutamic acid cooling crystallization process are performed to demonstrate the effectiveness and advantage of the proposed method.

Systematic Investigations on Continuous Fluidized Bed Crystallization for Chiral Separation

A recently developed continuous enantioseparation process utilizing two coupled fluidized bed crystallizers is systematically investigated to identify essential correlations between different operation parameters and the corresponding process performance on the example of asparagine monohydrate. Based on liquid phase composition and product crystal size distribution data, it is proven that steady state operation is achieved reproducibly in a relatively short time. The process outputs at steady state are compared for different feed flow rates, supersaturations, and crystallization temperatures. It is shown that purities &gt;97% are achieved with productivities up to 40 g/L/h. The size distribution, which depends almost exclusively on the liquid flow rate, can be easily adjusted between 260 and 330 µm (mean size) with an almost constant standard deviation of ±55 µm.

Fast Continuous Non-Seeded Cooling Crystallization of Glycine in Slug Flow: Pure α-Form Crystals with Narrow Size Distribution

Glycine has been widely used as pharmaceutical excipients and synthesis reagents, and commercial glycine has a significant amount of aggregation and wide particle size distribution. A simple but reproducible process for generating uniform glycine crystals is always desired for both product quality and process efficiency purposes. Continuous cooling crystallization of glycine has been carried out in air-liquid slug flow in millimeter ID tubing, starting from solution without using seeds. Slugs were formed by combining air and liquid streams, then went through the crash cooling zone of varying lengths (tubing length in contact with ice bags). The operational boundaries of crash cooling times were evaluated: natural cooling (lower bound, no crash cooling), maximum cooling time for pure α-form without aggregation (upper bound), and beyond upper bound. Non-aggregating pure α-form glycine crystals were continuously generated within ~ 10 min, feasible from multiple conditions (combinations of crashing cooling time and starting concentration). When crash cooling time further increases (while maintaining the starting concentration), crystal aggregations and/or γ-form crystals could appear. Reducing starting concentration can allow longer crash cooling time without widening product crystal size distribution or reducing crystalline form purity. At proper conditions, even natural cooling in slugs can nucleate and grow non-aggregated pure α-form crystals. All cooling conditions carried out in slug flow generally minimize needle-shaped crystals compared with corresponding batches. Glycine crystals of α-form and narrow size distribution can be continuously generated within 10 min from cooling crystallization in millimeter-sized slug flow, without using external seeds nor adding solvent/additives. And, the operational boundaries of crash cooling time (at proper starting concentrations) for pure α-form non-aggregating product crystals are identified.

Monitoring the Dynamics of a Continuous Sonicated Tubular Cooling Crystallizer

For the first time, continuous ultrasound assisted tubular crystallizer dynamics is studied in pilot scale operation. It is vital to understand process dynamics for continuous crystallizers as robust crystallization processes are developed. The mixing time using tracer impulses and experimental continuous crystallization runs to understand the performance of process variables, with focused beam reflectance measurement (FBRM), process video microscope measurements and off-line particle size analytics are reported. Model system was phthalic acid crystallization from water. The effect of power ultrasound and residence time on the crystallization dynamics and on the product crystal size distribution (CSD) were studied. The use of ultrasound was found to be vital in the crystallization operations in order to prevent pipe clogging. It was shown that ultrasound power increase improves mixing in tubular reactors, and it decreases the product CSD. Also, residence time increase decreases the CSD. It increases ultra...

Modeling of Membrane-Assisted Seeded Batch Crystallization

In this work, the operation of membrane-assisted seeded batch crystallization is modeled for five substances: potassium nitrate, potassium sulfate, pentaerythritol, succinic acid, and potassium alum. The effect of seed loading, seed size, and water removal rate on product crystal size is investigated. Seed loading and seed size were found to have a significant impact on product crystal size for a given batch time and product yield. Trajectories for the optimal water removal rate versus time were also determined. Overall, the results show that membrane-assisted crystallization behaves similarly to other types of crystallization in terms of product crystal size and size distribution while having the potential to reduce cost and equipment size.